## [1] "There were 41 instances where a person's residence town didn't match up with their injury town, out of 161 ODs in 2018 in region 3. This is 0.254658 of all ODs in this year."
## [1] "Here's a more in-depth look at out-of-town ODs in specific towns:"
## Town name Out-of-town ODs Total ODs Proportion of out-of-town ODs
## 1 Middletown 1 15 0.07
## 2 Norwich 2 12 0.17
## [1] "There were 33 instances where a person's residence town didn't match up with their injury town, out of 179 ODs in 2019 in region 3. This is 0.184358. "
## [1] "Here's a more in-depth look at out-of-town ODs in specific towns:"
## Town name Out-of-town ODs Total ODs Proportion of out-of-town ODs
## 1 Middletown 3 15 0.2
## 2 Norwich 5 26 0.19
## [1] "There were 29 instances where a person's residence town didn't match up with their injury town, out of 207 ODs in 2020 in region 3. This is 0.140097. "
## [1] "Here's a more in-depth look at out-of-town ODs in specific towns:"
## Town name Out-of-town ODs Total ODs Proportion of out-of-town ODs
## 1 Middletown 1 25 0.04
## 2 Norwich 4 34 0.12
## [1] "There were 43 instances where a person's residence town didn't match up with their injury town, out of 218 ODs in 2021 in region 3. This is 0.197248. "
## [1] "Here's a more in-depth look at out-of-town ODs in specific towns:"
## Town name Out-of-town ODs Total ODs Proportion of out-of-town ODs
## 1 Middletown 2 25 0.08
## 2 Norwich 6 24 0.25
## [1] "There were 27 instances where a person's residence town didn't match up with their injury town, out of 174 ODs in 2022 in region 3. This is 0.155172. "
## [1] "Here's a more in-depth look at out-of-town ODs in specific towns:"
## Town name Out-of-town ODs Total ODs Proportion of out-of-town ODs
## 1 Middletown 3 15 0.2
## 2 Norwich 4 32 0.12
## [1] "There were 115 people who OD'd in their own residence."
## [1] "The proportion of decedents ODing in their own residence was 0.684524."
## [1] "Out of everyone who OD'd in a residence, 0.804196 of people OD'd in their own residence."
## [1] "There were 134 people who OD'd in their own residence."
## [1] "The proportion of decedents ODing in their own residence was 0.736264."
## [1] "Out of everyone who OD'd in a residence, 0.853503 of people OD'd in their own residence."
## [1] "There were 158 people who OD'd in their own residence."
## [1] "The proportion of decedents ODing in their own residence was 0.748815."
## [1] "Out of everyone who OD'd in a residence, 0.863388 of people OD'd in their own residence."
## [1] "There were 159 people who OD'd in their own residence."
## [1] "The proportion of decedents ODing in their own residence was 0.685345."
## [1] "Out of everyone who OD'd in a residence, 0.811224 of people OD'd in their own residence."
## [1] "There were 128 people who OD'd in their own residence."
## [1] "The proportion of decedents ODing in their own residence was 0.688172."
## [1] "Out of everyone who OD'd in a residence, 0.831169 of people OD'd in their own residence."
## Rows: 5
## Columns: 32
## Groups: cocaine, combo..her.pharm.or.fent..OR.pharm.fent, heronly, pharmonly, fentonly, heroin, X6.mam, morphine, hermor_nocod, codeine, cod_w_no_hermor, di.H.codeine, hydromorphone, oxymorphone, hydrocodone, oxycodone, methadone, buprenorphine, fentanyl..4ANPP.too., Frankens, fent.or.frankens, tramadol, opioid.analogs..e.g...U47700., otherop, pharma_w_meth_no_fent.or.op.analogs.or.cod.or..other.op., pharma_nobupnometh, other, benzos, amphetamine, EtOH [4]
## $ cocaine <int> 0, 0, 0, 1, 1
## $ combo..her.pharm.or.fent..OR.pharm.fent <int> 0, 0, 0, 0, 0
## $ heronly <int> 0, 0, 0, 0, 0
## $ pharmonly <int> 0, 0, 0, 0, 0
## $ fentonly <int> 1, 1, 1, 1, 1
## $ heroin <int> 0, 0, 0, 0, 0
## $ X6.mam <int> 0, 0, 0, 0, 0
## $ morphine <int> 0, 0, 0, 0, 0
## $ hermor_nocod <int> 0, 0, 0, 0, 0
## $ codeine <int> 0, 0, 0, 0, 0
## $ cod_w_no_hermor <int> 0, 0, 0, 0, 0
## $ di.H.codeine <int> 0, 0, 0, 0, 0
## $ hydromorphone <int> 0, 0, 0, 0, 0
## $ oxymorphone <int> 0, 0, 0, 0, 0
## $ hydrocodone <int> 0, 0, 0, 0, 0
## $ oxycodone <int> 0, 0, 0, 0, 0
## $ methadone <int> 0, 0, 0, 0, 0
## $ buprenorphine <int> 0, 0, 0, 0, 0
## $ fentanyl..4ANPP.too. <int> 1, 1, 1, 1, 1
## $ Frankens <int> 0, 0, 0, 0, 1
## $ fent.or.frankens <int> 1, 1, 1, 1, 1
## $ tramadol <int> 0, 0, 0, 0, 0
## $ opioid.analogs..e.g...U47700. <int> 0, 0, 0, 0, 0
## $ otherop <int> 0, 0, 0, 0, 0
## $ pharma_w_meth_no_fent.or.op.analogs.or.cod.or..other.op. <int> 0, 0, 0, 0, 0
## $ pharma_nobupnometh <int> 0, 0, 0, 0, 0
## $ other <int> 0, 0, 1, 0, 0
## $ benzos <int> 0, 0, 0, 0, 0
## $ amphetamine <int> 0, 0, 0, 0, 0
## $ EtOH <int> 0, 0, 0, 0, 0
## $ THC <int> 0, 1, 1, 0, 1
## $ n <int> 11, 5, 4, 4, 4
The top 5 substance combinations for 2018 are:
## Rows: 5
## Columns: 33
## Groups: xyla, combo, heronly, pharmonly, fentonly, Heroin, X6.mam, Morphine, hermor_nocod, Codeine, cod.w.no.hermor, di.H.codeine, Hydromorphone, oxymorphone, Hydrocodone, Oxycodone, Methadone, bup, fentanyl..4.ANPP.too., frankens, fent...frankens, tramadol, opioid.analogs..e.g...U47700., Other.Op, pharma.w.meth.bup.no.fent.or.other.op, pharma_nobupnometh, other, benzos, cocaine, amphetamine, EtOH [4]
## $ xyla <int> 0, 0, 0, 0, 0
## $ combo <int> 0, 0, 0, 0, 0
## $ heronly <int> 0, 0, 0, 0, 0
## $ pharmonly <int> 0, 0, 0, 0, 0
## $ fentonly <int> 1, 1, 1, 1, 1
## $ Heroin <int> 0, 0, 0, 0, 0
## $ X6.mam <int> 0, 0, 0, 0, 0
## $ Morphine <int> 0, 0, 0, 0, 0
## $ hermor_nocod <int> 0, 0, 0, 0, 0
## $ Codeine <int> 0, 0, 0, 0, 0
## $ cod.w.no.hermor <int> 0, 0, 0, 0, 0
## $ di.H.codeine <int> 0, 0, 0, 0, 0
## $ Hydromorphone <int> 0, 0, 0, 0, 0
## $ oxymorphone <int> 0, 0, 0, 0, 0
## $ Hydrocodone <int> 0, 0, 0, 0, 0
## $ Oxycodone <int> 0, 0, 0, 0, 0
## $ Methadone <int> 0, 0, 0, 0, 0
## $ bup <int> 0, 0, 0, 0, 0
## $ fentanyl..4.ANPP.too. <int> 1, 1, 1, 1, 1
## $ frankens <int> 0, 0, 0, 0, 0
## $ fent...frankens <int> 1, 1, 1, 1, 1
## $ tramadol <int> 0, 0, 0, 0, 0
## $ opioid.analogs..e.g...U47700. <int> 0, 0, 0, 0, 0
## $ Other.Op <int> 0, 0, 0, 0, 0
## $ pharma.w.meth.bup.no.fent.or.other.op <int> 0, 0, 0, 0, 0
## $ pharma_nobupnometh <int> 0, 0, 0, 0, 0
## $ other <int> 1, 0, 0, 0, 0
## $ benzos <int> 0, 0, 0, 0, 0
## $ cocaine <int> 1, 0, 0, 1, 1
## $ amphetamine <int> 0, 0, 0, 0, 0
## $ EtOH <int> 1, 0, 1, 0, 0
## $ THC <int> 0, 1, 0, 1, 0
## $ n <int> 7, 6, 6, 6, 5
The top 5 substance combinations for 2019 are:
## Rows: 5
## Columns: 32
## Groups: combo, heronly, pharmonly, fentonly, Heroin, X6.mam, Morphine, hermor_nocod, Codeine, cod.w.no.hermor, di.H.codeine, Hydromorphone, oxymorphone, Hydrocodone, Oxycodone, Methadone, bup, fentanyl..4.ANPP.too., frankens, fent...frankens, tramadol, opioid.analogs..e.g...U47700., Other.Op, pharma.w.meth.bup.no.fent.or.other.op, pharma_nobupnometh, other, benzos, cocaine, amphetamine, EtOH [4]
## $ combo <chr> "0", "0", "0", "0", "0"
## $ heronly <chr> "0", "0", "0", "0", "0"
## $ pharmonly <chr> "0", "0", "0", "0", "0"
## $ fentonly <chr> "1", "1", "1", "1", "1"
## $ Heroin <dbl> 0, 0, 0, 0, 0
## $ X6.mam <dbl> 0, 0, 0, 0, 0
## $ Morphine <dbl> 0, 0, 0, 0, 0
## $ hermor_nocod <dbl> 0, 0, 0, 0, 0
## $ Codeine <dbl> 0, 0, 0, 0, 0
## $ cod.w.no.hermor <dbl> 0, 0, 0, 0, 0
## $ di.H.codeine <dbl> 0, 0, 0, 0, 0
## $ Hydromorphone <dbl> 0, 0, 0, 0, 0
## $ oxymorphone <dbl> 0, 0, 0, 0, 0
## $ Hydrocodone <dbl> 0, 0, 0, 0, 0
## $ Oxycodone <dbl> 0, 0, 0, 0, 0
## $ Methadone <dbl> 0, 0, 0, 0, 0
## $ bup <dbl> 0, 0, 0, 0, 0
## $ fentanyl..4.ANPP.too. <dbl> 1, 1, 1, 1, 1
## $ frankens <dbl> 0, 0, 0, 0, 0
## $ fent...frankens <dbl> 1, 1, 1, 1, 1
## $ tramadol <dbl> 0, 0, 0, 0, 0
## $ opioid.analogs..e.g...U47700. <dbl> 0, 0, 0, 0, 0
## $ Other.Op <dbl> 0, 0, 0, 0, 0
## $ pharma.w.meth.bup.no.fent.or.other.op <dbl> 0, 0, 0, 0, 0
## $ pharma_nobupnometh <dbl> 0, 0, 0, 0, 0
## $ other <dbl> 1, 1, 0, 0, 1
## $ benzos <dbl> 0, 0, 0, 0, 0
## $ cocaine <dbl> 0, 0, 0, 0, 1
## $ amphetamine <dbl> 0, 0, 0, 0, 0
## $ EtOH <dbl> 1, 0, 0, 0, 0
## $ THC <dbl> 0, 0, 0, 1, 0
## $ n <int> 13, 12, 9, 9, 9
The top 5 substance combinations for 2020 are:
## Rows: 5
## Columns: 32
## Groups: combo, her.only, pharm.only, fent.only, Heroin, X6.mam, Morphine, hermor_nocod, Codeine, cod.w.no.hermor, di.H.codeine, Hydromorphone, oxymorphone, Hydrocodone, Oxycodone, Methadone, bup, fentanyl..4.ANPP.despropionyl.fent.too., frankens, fent...frankens, tramadol, opioid.analogs.e.g.mitragynine, Other.Op, pharma.w.meth.bup.no.fent.or.other.op, pharma_nobupnometh, other, benzos, cocaine, amphetamine..including.eutylone., EtOH [4]
## $ combo <int> 0, 0, 0, 0, 0
## $ her.only <int> 0, 0, 0, 0, 0
## $ pharm.only <int> 0, 0, 0, 0, 0
## $ fent.only <int> 1, 1, 1, 1, 1
## $ Heroin <int> 0, 0, 0, 0, 0
## $ X6.mam <int> 0, 0, 0, 0, 0
## $ Morphine <int> 0, 0, 0, 0, 0
## $ hermor_nocod <int> 0, 0, 0, 0, 0
## $ Codeine <int> 0, 0, 0, 0, 0
## $ cod.w.no.hermor <int> 0, 0, 0, 0, 0
## $ di.H.codeine <int> 0, 0, 0, 0, 0
## $ Hydromorphone <int> 0, 0, 0, 0, 0
## $ oxymorphone <int> 0, 0, 0, 0, 0
## $ Hydrocodone <int> 0, 0, 0, 0, 0
## $ Oxycodone <int> 0, 0, 0, 0, 0
## $ Methadone <int> 0, 0, 0, 0, 0
## $ bup <int> 0, 0, 0, 0, 0
## $ fentanyl..4.ANPP.despropionyl.fent.too. <int> 1, 1, 1, 1, 1
## $ frankens <int> 0, 0, 0, 0, 0
## $ fent...frankens <int> 1, 1, 1, 1, 1
## $ tramadol <int> 0, 0, 0, 0, 0
## $ opioid.analogs.e.g.mitragynine <int> 0, 0, 0, 0, 0
## $ Other.Op <int> 0, 0, 0, 0, 0
## $ pharma.w.meth.bup.no.fent.or.other.op <int> 0, 0, 0, 0, 0
## $ pharma_nobupnometh <int> 0, 0, 0, 0, 0
## $ other <int> 1, 0, 1, 1, 1
## $ benzos <int> 0, 0, 0, 0, 0
## $ cocaine <int> 1, 1, 1, 1, 0
## $ amphetamine..including.eutylone. <int> 0, 0, 0, 0, 0
## $ EtOH <int> 0, 0, 0, 1, 1
## $ THC <int> 0, 0, 1, 0, 0
## $ n <int> 19, 13, 12, 10, 9
The top 5 substance combinations for 2021 are:
## Rows: 5
## Columns: 32
## Groups: combo, her.only, pharm.only, fent.only, Heroin, X6.mam, Morphine, hermor_nocod, Codeine, cod.w.no.hermor, di.H.codeine, Hydro.morphone, oxy.morphone, Hydro.codone, Oxy.codone, Methadone, bup, fentanyl..4.ANPP.despropionyl.fent.too., frankens, fent...frankens, tramadol, opioid.analogs.e.g.mitragynine, Other.Op, pharma.w.meth.bup.no.fent.or.other.op, pharma_nobupnometh, other, benzos, cocaine, amphetamine.including.eutylone.MDMA, EtOH [5]
## $ combo <int> 0, 0, 0, 0, 0
## $ her.only <int> 0, 0, 0, 0, 0
## $ pharm.only <int> 0, 0, 0, 0, 0
## $ fent.only <int> 1, 1, 1, 1, 1
## $ Heroin <int> 0, 0, 0, 0, 0
## $ X6.mam <int> 0, 0, 0, 0, 0
## $ Morphine <int> 0, 0, 0, 0, 0
## $ hermor_nocod <int> 0, 0, 0, 0, 0
## $ Codeine <int> 0, 0, 0, 0, 0
## $ cod.w.no.hermor <int> 0, 0, 0, 0, 0
## $ di.H.codeine <int> 0, 0, 0, 0, 0
## $ Hydro.morphone <int> 0, 0, 0, 0, 0
## $ oxy.morphone <int> 0, 0, 0, 0, 0
## $ Hydro.codone <int> 0, 0, 0, 0, 0
## $ Oxy.codone <int> 0, 0, 0, 0, 0
## $ Methadone <int> 0, 0, 0, 0, 0
## $ bup <int> 0, 0, 0, 0, 0
## $ fentanyl..4.ANPP.despropionyl.fent.too. <int> 1, 1, 1, 1, 1
## $ frankens <int> 0, 0, 0, 0, 0
## $ fent...frankens <int> 1, 1, 1, 1, 1
## $ tramadol <int> 0, 0, 0, 0, 0
## $ opioid.analogs.e.g.mitragynine <int> 0, 0, 0, 0, 0
## $ Other.Op <int> 0, 0, 0, 0, 0
## $ pharma.w.meth.bup.no.fent.or.other.op <int> 0, 0, 0, 0, 0
## $ pharma_nobupnometh <int> 0, 0, 0, 0, 0
## $ other <int> 1, 1, 0, 1, 0
## $ benzos <int> 0, 0, 0, 0, 0
## $ cocaine <int> 1, 0, 1, 0, 1
## $ amphetamine.including.eutylone.MDMA <int> 0, 0, 0, 0, 0
## $ EtOH <int> 0, 0, 1, 1, 0
## $ THC <int> 0, 0, 0, 0, 0
## $ n <int> 14, 12, 9, 9, 8
The top 5 substance combinations for 2022 are:
I identify chronic users crudely – I look for entries where the words “chronic” [can sometimes indicate chronic pain, meaning opioid scripts], “Chronic”, “user”, “drug use”, “drug user”, “drug abuse”, “snort”, “snorts”, “drug abuse”, “addict”, “addicted”, “rehab”, “sober house”, “clean” or “abuse” pops up in either the notes field or immediate cause of death, because that generally means that the person had chronic drug use [based on my look at the data]
## [1] "There were at least 67 people with known chronic use out of 168 decedents in 2018, which is 39.880952 percent of all decedents."
## [1] "There were at least 73 people with known chronic use out of 182 decedents in 2019, which is 40.109890 percent of all decedents."
## [1] "There were at least 128 people with known chronic use out of 211 decedents in 2020, which is 60.663507 percent of all decedents."
## [1] "There were at least 126 people with known chronic use out of 232 decedents in 2021, which is 54.310345 percent of all decedents."
## [1] "There were at least 103 people with known chronic use out of 186 decedents in 2022, which is 55.376344 percent of all decedents."
Please note: this field and all fields explored below are only available up to 2020.
## [1] "There were 130 people found within 24 hours, which is 0.773810 of all decedents."
## [1] "There were 26 people found in over 24 hours, which is 0.154762 of all decedents."
## [1] "There were 139 people found within 24 hours, which is 0.763736 of all decedents."
## [1] "There were 32 people found in over 24 hours, which is 0.175824 of all decedents."
## [1] "There were 161 people found within 24 hours, which is 0.763033 of all decedents."
## [1] "There were 39 people found in over 24 hours, which is 0.184834 of all decedents."
Under 24h
Over 24h
Under 24h
Over 24h
Under 24h
Over 24h
Under 24h
Over 24h
Under 24h
Over 24h
Under 24h
Over 24h
Under 24h
Over 24h
Under 24h
Over 24h
Under 24h
Over 24h